The Gaussian process latent variable model (GP-LVM) is a powerful approach for probabilistic modelling of high dimensional data through dimensional reduction. In this paper we ext...
Abstract — This paper describes a practical technique for the optimal scheduling of control dominated systems minimizing the weighted average latency over all control branches. S...
— Coalescence is the problem of isolated mobile robots independently searching for peers with the goal of forming a single connected network. This is important because communicat...
Multiplysectioned Bayesian networks provide a probabilistic framework for reasoning about uncertain domains in cooperative multiagent systems. Several advances have been made in r...
Background model and tracking became critical components for many vision-based applications. Typically, background modeling and object tracking are mutually independent in many ap...